VALIDATION OF CARTOSAT-1 DTM GENERATION FOR THE SALON DE
PROVENCE TEST SITE
Marco Gianinetto a, *, Francesco Fassi b
a
Politecnico di Milano, Remote Sensing Laboratory, DIIAR Dept., Piazza Leonardo Da Vinci 32, 20133 Milano, Italy
– marco.gianinetto@polimi.it
b
Politecnico di Milano, Elab3D Poli, DIIAR Dept., Piazza Leonardo Da Vinci 32, 20133 Milano, Italy –
francesco.fassi@polimi.it
Commission I, SS-11
KEY WORDS: Satellite remote sensing, Digital elevation models, Space photogrammetry, Accuracy analysis, Topographic
mapping
ABSTRACT:
Cartosat-1 is the eleventh satellite of the Indian Space Research Organisation series and is primarily meant for topographic mapping
and Digital Terrain Model (DTM) generation. In the framework of the Cartosat-1 Scientific Assessment Programme, the Politecnico
di Milano University (Italy) evaluated as Co-Investigator the performances of the Cartosat-1 satellite in the generation of DTMs.
This paper describes the outcomes for the Salon de Provence test site (France) with respect to existing standards and products
actually used in France and also provides a comparison with the global Shuttle Radar Topography Mission’s DTM supplied by
NASA and widely used in the remote sensing community.
1. INTRODUCTION
The Indian Space Research Organisation (ISRO) launched the
Cartosat-1 satellite on May 05, 2005. The satellite was
primarily designed for topographic mapping and has two
panchromatic Charge Coupled Device (CCD) sensors, both with
a spatial resolution of 2.5m: i) the Fore camera, pointing +26
degrees with respect to the nadir, and ii) the Aft camera,
pointing -5 degrees with respect to the nadir. These sensors can
either acquire along-track stereo images with a 27.5km swath
and a base to height ratio (B/H) of 0.6 or mono images with a
combined swath of 55km (Indian Space Research Organisation,
2008).
At the beginning of 2006 an agreement has been reached
between the International Society for Photogrammetry and
Remote Sensing (ISPRS) and ISRO to jointly conduct the
Cartosat-1 Scientific Assessment Programme (C-SAP). The aim
of the C-SAP was to assess the mapping capabilities of the
Cartosat-1 satellite, especially with respect to the generation of
Digital Terrain Models (DTMs) for different types of terrain.
As Co-Investigator in the C-SAP, the Politecnico di Milano
University (Italy) evaluated the performances of DTM
generation from Cartosat-1 stereo data for the Salon de
Provence (France) test site (C-SAP TS4). The investigation was
carried on with respect to existing standards and products
actually used in France (i.e., the French Institut Géographique
National’s and Spot Image’s Reference 3D®, and the French
®DB Alti). Moreover, the investigation also provided a
comparison with the global Shuttle Radar Topography Mission
(SRTM) DTM supplied by NASA and widely used in the
remote sensing community.
Imagery collected with Cartosat-1 were used for the generation
of medium-resolution (25m grid cell size) and low-resolution
(90m grid cell size) DTMs using commercial off-the-shelf
software, so to provide comprehensive and operative hints to
final users.
2. DATASET
2.1 C-SAP dataset composition
The standard C-SAP TS4 dataset delivered to the investigating
teams was composed of the following items:
ƒ
One 2.5m Cartsat-1 stereo pair collected over Salon
de Provence (France) on February 6, 2006
(Path=0128, Row=0198) and provided by ISRO;
ƒ
A set of 22 Ground Control Points (GCPs) provided
by the Principal-Investigator (PI) French Institut
Géographique National (IGN);
ƒ
One 19m x 26m resolution reference DTM
(MNT_DBTOPO® DTM) with IGN69 datum for
heights, provided by the PI.
In addition to the standard C-SAP TS4 dataset, it was also used
a raster SRTM DTM made available from NASA (National
Aeronautics and Space Administration, 2008).
2.2 Standard accuracy of Cartsat-1 images
ISRO delivered to the investigating teams Cartosat-1 imagery
as Stereo Orthokit product in the GeoTIFF format (Figure 1)
and also supplied predetermined Rational Polynomial
Coefficients (Indian Space Research Organisation, 2005). The
GeoTIFF Orthokit product is radiometrically corrected and is
supplied to produce high precision cartographic products and
DTMs: its location accuracy is better than 250m (3σ=220m for
* Corresponding author.
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system level correction, Level 1) (Krishnaswamy and
Kalyanaraman, 2002; National Remote Sensing Agency, 2007).
plan and better than 2.5m in elevation (Gachet and Favé, 2006).
Figure 2 shows the GCPs’ distribution on the study area.
2.3 Standard accuracy of references DTMs
3. DATA PROCESSING
The Root Mean Square Error (RMSE) is a measure often used
to assess the accuracy of elevation data and is defined as
follows:
n
∑ (ΔZ )
2
i
RMSE =
i =1
n
(1)
where:
ΔZi are the elevation residuals (i.e., the differences of the
elevation measures with respect to reference data)
n is the number of measures
Another statistics often used to evaluate the overall accuracy of
elevation data at a fixed confidence level (α) is the Linear Error
(LEα). LEα performs a comparison in the elevation data
towards reference measures: an LE90=2.5m implies that 90% of
the measures to be tested vary from the reference measures by
2.5m or less.
Accuracies of references DTMs is shown as follows:
ƒ
MNT_DBTOPO® DTM: RMSE=1m in elevation
over the whole France, as from PI IGN specifications;
ƒ
SRTM DTM: absolute LE90=6.2m in elevation for
Eurasia (Rodriguez et al., 2006).
2.4 Standard accuracy of references GCPs
The GCPs supplied by the PI IGN were derived from the
French BD_ORTHO® and had an accuracy better than 1.5m in
The Cartosat-1 data processing was done using ENVI 4.3®. A
commercial off-the-shelf software was selected for
investigating the capabilities and limits of the system in the
DTM’s generation using standard image processing tools, so
from the point of view of a typical remote sensing user. The
data processing involved the following aspects: i) preprocessing, ii) optimization of the DTM’s extraction procedure
and, iii) analysis of the influence of GCPs in the modelled
DTMs.
3.1 Data pre-processing
All the dataset were first converted into the UTM-WGS84
F31N reference system. The MNT_DBTOPO® DTM was
resampled from its original 19m x 26m cell resolution to 25m x
25m and the SRTM DTM from its original 60m x 90m cell
resolution to 90m x 90m.
3.2 Optimization of the DTM’s extraction procedure
Before generating the DTMs from the Cartosat-1 images it was
investigated the influence of the parameters involved in the
generation process (i.e., number of tie points used, search
window and moving window sizes, correlation coefficient and
terrain detail). A sensitivity analysis led to the final optimal
configuration as shown in Table 1.
Sixty tie points were used in all the tests. They have been
automatically detected using a regular grid scheme covering the
entire images, obtaining an Y parallax of 1.27 pixel
(corresponding to 3.18m). By increasing the number of tie
points, it was not observed any improvement in the Y parallax.
(a)
(b)
Figure 1. Cartosat-1 stereo orthokit collected over Salon de Provence (France) on February 6, 2006. (a) 2.5m Aft panchromatic
image, (b) 2.5m Fore panchromatic image.
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Parameter
Number of tie points
Search window size
Moving window size
Correlation coefficient
Terrain detail
particular emphasis for the second. With respect to the former,
the accuracy of the DTMs were also verified for geocoded
rDTMs (geocoded after the generation process), while for the
latter it was deeply studied the influence of the GCPs (number
and the geometric distribution) on the DTM’s accuracy.
Value
60
800 pixel
30 pixel
> 0.8
level 6 (over 7 levels)
4. RESULTS AND DISCUSSION
Table 1. Optimization of the DTM’s automatic extraction
procedure.
4.1 Medium-resolution DTM generation
4.1.1 The influence of GCPs in the generation of relative
DTMs:
When generating relative DTMs, the output is not correctly
georeferenced and elevation data are referred to an arbitrary
plane. Thus, without properly geocoding the error (in the z
coordinate) of the Cartosat-1 rDTM was observed to be many
hundreds of meters. After georeferencing the rDTMs using 5
GCPs of the original C-SAP dataset, the vertical accuracy
drastically increased to less than 20m (LE90).
The DTM’s accuracy was tested at two different scales: i) at
local level using as Independent Check Points (ICPs) the
remaining 17 GCPs of the original C-SAP dataset, and ii) at
global scale using the MNT_DBTOPO® DTM as ground truth
for the whole test site.
Figure 2. Ground control points distribution over the study area.
One of the major factor determining the accuracy of the
generated DTM, as well as the processing time needed for its
generation, is the ‘terrain detail level’ parameter. Since the
DTM extraction is carried out by means of automatic image
matching to find homologous features on the Aft and Fore
images of the stereo pair, the terrain detail level determines the
number of image pyramids used during the image matching.
The use of the ‘minimum terrain detail level’ stops the process
after the coarsest level of the image matching, while the use of
the ‘maximum terrain detail level’ iterates until the image
matching is performed at the highest resolution as possible.
In this study it was observed that the use of terrain detail level 6,
instead of the maximum level (level 7), reduced the computing
time by a factor of 4.6 without any sensible decrease in the final
DTM’s accuracy.
3.3 Ground control points selection
Because the satellite’s pointing and ephemeris information are
often inadequate for their use in applications involving highresolution imagery, DTMs must be referenced to a map
coordinate system using GCPs (Lang, 1999). The use of GCPs
in the DTM generation process brings to the so called ‘absolute
DTMs’, where ‘absolute’ means that the terrain’s elevation
values are referred to a geodetic datum.
For geocoded rDTMs, results showed no significant difference
in the mean value of residuals (μ) for both the comparison to
the ICPs and the MNT_DBTOPO® DTM, respectively 4.33m
and 4.24m. On the contrary, this is not true for standard
deviation (σ), RMSE and LE90, which showed higher values
when computed with respect to MNT_DBTOPO® DTM
(σ=13.55m, RMSE=14.19m and LE90=19.00m), indicating that
the statistics of the ICPs (σ=8.09m, RMSE=9.02m and
LE90=16.10m) could not be assumed as a correct term of
comparison for the complete elevation range.
4.1.2 The influence of GCPs in the generation of absolute
DTMs:
When generating absolute DTMs, the number and geometric
distribution of the GCPs have a great impact in the final DTM’s
accuracy. For this reason, the original set of 22 GCPs was
divided into a first subset of j GCPs used for the DTM’s
georeferencing and a second subset of 22-j ICPs used for the
evaluation of results.
Several tests have been done, varying j form 2 to 22 to find the
optimum number of GCPs to be used. Table 2 shows a
summary of results.
When no GCPs are available it is still possible to produce
DTMs from stereo pairs by means of automatic image matching
algorithms,. In this case the so called ‘relative DTMs’ will be
produced, where ‘relative’ means that the terrain’s elevation
values are not referred to a geodetic datum but to an arbitrary
plane (e.g., the lowest value in the scene).
With the exception of test #5, the comparison of the Cartosat-1
aDTM with the ICPs showed a RMSE between 1.41m using 9
GCPs (for test #14) and 5.17m using 2 GCPs (for test #3), while
the LE90 was between 1.91m using 6 GCPs (for test #11) and
8.91m using 2 GCPs (for tests #2 and #3). Even if the observed
mean values of residuals were small and between -0.12m (for
test #13) and -2.80m (for test #3), they were not null, thus
indicating a small bias in the output data. Regarding their
standard deviation, the observed values were between 1.36m
(for test #11) and 4.49m (for test #1).
This study investigated the DTM’s generation for both the
relative (rDTM) and the absolute (aDTMs) methods, with
The best overall performance was obtained for test #14 using 9
GCPs (μ=0.47m, σ=1.39m, RMSE=1.41m and LE90=2.77m),
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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B1. Beijing 2008
thought also using fewer GCPs (tests #13, #11 and #9) similar
results were achieved (Table 2). Even if using only 4 GCPs (test
#9) led to better result in terms of LE90 (1.91m), altogether it
gave worst performances and produced more biased results (μ=1.03 m, σ=1.59m, RMSE=1.67m) than the previous.
The minimum number of GCPs necessary to obtain a good
DTM was determined to be three (test #5). Using this
configuration it was obtained a mean value of residuals of
1.15m, a standard deviation of 1.97m, a RMSE of 2.24m and a
LE90 of 3.23m, which are 58.9% and 16.6% worst if compared
to the best one, respectively in terms of RMSE and LE90.
Comparing the Cartosat-1 aDTM with the MNT_DBTOPO®
DTM it was observed a similar behaviour than that described
above. Generally speaking, increasing the number of GCPs the
aDTM’s residuals decreased until the values of μ=-1.22m,
σ=6.79m, RMSE=6.90m and LE90=10.00m (for test #14).
Once again, the use of three GCPs (test #5) gave good results.
In any case, no significant improvement was observed using
more than 9 GCPs both when comparing results with the ICPs
and with the MNT_DBTOPO® DTM. Table 3 shows a
summary of results.
4.1.3 The influence of the terrain’s elevation and slope:
Once optimized both the algorithm’s parameters and the
configuration of the GCPs used in the generation process, two
aDTMs were selected as ‘best DTMs’ (test #5 and test #14) and
further analysis was carried on to study the DTM’s accuracy
with respect to the terrain’s elevation and slope characteristics.
Regarding the first issue, both the aDTMs behaved similarly
and in near flat terrain they showed a high accuracy
(RMSE<4.49m and LE<7.00m). With increasing the elevation
the RMSE and LE90 rapidly increased until values of 17.74m
and 29.00m for test #14 and 16.45m and 28.00m for test #5,
respectively.
Regarding the influence of the terrain’s slope, again both the
Test
ID
1
2
3
4
5
6
7
8
9
10
11
12
13
14
GCPs
(nr.)
2
2
2
3
3
3
4
4
4
5
6
7
8
9
15
22
GCPs configuration
UR, LL
UL, LR,
LR, LL
UL, LL, LR
C, LR, LL
C, UL, UR
UL, UR, LL, LR
C, UR, LL, LR
C, UR, LL, UL
C, UL, UR, LL, LR
UL, UR, LL, LR, RC, LC
C, UL, UR, LL, LR, RC, LC
UL, UR, LL, LR, RC, LC, C, CL
UL, UR, LL, LR, RC, LC, C, CL,
CR
all
ICPs
(nr.)
20
20
20
19
19
19
18
18
18
17
16
15
14
13
μ (m
)
-1.50
-2.46
-2.80
-2.12
1.15
1.82
-1.52
-0.63
-0.31
9.26
-1.03
-1.46
-0.12
0.47
σ (m
)
4.49
3.90
4.47
2.15
1.97
2.63
1.80
2.24
1.59
2.50
1.36
1.68
1.64
1.39
|μ|
(m)
3.47
3.36
3.78
2.43
1.77
2.82
1.78
1.95
1.31
9.26
1.21
1.59
1.26
1.23
RMSE
(m)
4.63
4.53
5.17
2.98
2.24
3.14
2.32
2.27
1.58
9.57
1.67
2.18
1.58
1.41
LE90
(m)
7.91
8.91
8.91
4.91
3.23
4.70
3.97
2.98
2.97
13.38
1.91
4.70
3.77
2.77
0
0.47
1.61
1.39
1.64
2.38
C=centre image, UR=upper right, UL=upper left, LR=lower right, LL=lower left, RC=right centre, LC=left centre, CU=centre upper, CL=centre
lower, all=all the 22 available GCPs.
Table 2. Accuracy of the Cartosat-1 absolute DTM. Statistics on residuals computed with respect to the Independent Check
Points.
Test
ID
1
2
3
4
5
6
7
8
9
10
11
12
13
14
GCPs
(nr.)
2
2
2
3
3
3
4
4
4
5
6
7
8
9
15
22
GCPs configuration
ICPs
(nr.)
20
20
20
19
19
19
18
18
18
17
16
15
14
13
UR, LL
UL, LR,
LR, LL
UL, LL, LR
C, LR, LL
C, UL, UR
UL, UR, LL, LR
C, UR, LL, LR
C, UR, LL, UL
C, UL, UR, LL, LR
UL, UR, LL, LR, RC, LC
C, UL, UR, LL, LR, RC, LC
UL, UR, LL, LR, RC, LC, C, CL
UL, UR, LL, LR, RC, LC, C, CL,
CR
all
0
μ (m σ (m
)
)
-1.84 8.09
-2.86 7.77
-3.14 7.52
-3.57 6.70
-0.43 6.43
-0.02 7.47
-3.08 6.98
-1.94 6.87
-1.72 7.10
8.06 10.00
-2.24 7.10
-2.81 7.07
-1.69 6.98
-1.22 6.79
|μ|
(m)
8.30
8.28
8.15
7.59
6.45
7.47
7.63
7.14
7.31
12.85
7.44
7.61
7.18
6.90
RMSE
(m)
12.00
12.00
12.00
11.00
9.00
10.00
11.00
10.00
10.00
16.00
10.00
11.00
10.00
10.00
LE90
(m)
-1.84
-2.86
-3.14
-3.57
-0.43
-0.02
-3.08
-1.94
-1.72
8.06
-2.24
-2.81
-1.69
-1.22
-0.76
6.86
9.00
-0.76
6.81
C=centre image, UR=upper right, UL=upper left, LR=lower right, LL=lower left, RC=right centre, LC=left centre, CU=centre upper, CL=centre
lower, all=all the 22 available GCPs.
Table 3. Accuracy of the Cartosat-1 absolute DTM. Statistics on residuals computed with respect to the French DTM
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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B1. Beijing 2008
aDTMs behaved similarly and in near flat terrain they showed a
high accuracy (RMSE<4.52m and LE<7.00m). With increasing
the slope the RMSE and LE90 rapidly increased until
unacceptable values (greater than 22.00m for the RMSE and
greater than 35.00m for the LE in the range of 30°-40° for
slopes). It is to be noted that for the Salon de Provence test site
94.12% of samples had a slope less than 20°, consequently the
resulting DTM’s accuracy was better than 10.74m for RMSE
and better than 17.00m for LE90.
Another term of comparison used for evaluating the DTM’s
performances were the requirements for IGN’s and Spot
Image’s Reference 3D®. The Reference 3D® is a DTM
generated using automatic correlation from SPOT-5/HRS data.
Its specifications are given in Table 4 (Buillon et al., 2006).
As shown in Table 5, the Cartosat-1 aDTM fulfilled the
Reference 3D® requirements while the rDTM did not.
4.2 Low- resolution DTM generation
The performances of the Cartosat-1 satellite were also tested for
the generation of low-resolution DTM (90m grid resolution).
As term of comparison it were used:
ƒ
The NASA’s SRTM DTM;
ƒ
The MNT_DBTOPO® DTM downsampled to a 90m
cell resolution;
ƒ
A set of ICPs extracted from the original C-SAP
dataset.
Results show that the 90-meters Cartosat-1 aDTMs performed
better than the SRTM DTM and overcome the SRTM’s
specifications, while the 90-meters Cartosat-1 rDTM poorly
performed and did not met the SRTM’s specifications.
Regarding the comparison to the higher precision ICPs, the best
results were obtained for test #14 (μ=-0.12m, σ=3.16m,
RMSE=3.09m and LE90=4.09m), followed by test #5
(μ=0.69m, σ=3.32m, RMSE=3.32m and LE90=5.34m) and the
SRTM performed worse (μ=0.51m, σ=3.37m, RMSE=3.33m
and LE90=7.38m).
Even if looking at mean values of residuals, standard deviations
and RMSEs the Cartosat-1 aDTM and the SRTM have similar
values, the former is more accurate in terms of LE90: that
means that the Cartosat-1 low-resolution aDTM has fewer gross
errors than the SRTM.
Parameter
DEM resolution
Specifications
1arc second (~30m on the Equator;
21m at 45° of latitude)
15m at 90% confidence level
Planimetric
absolute accuracy
Altimetric
10m at 90% confidence level, for
absolute accuracy slopes lower than 20%
18m at 90% confidence level, for
slopes included in 20% and 40%
30m at 90% confidence level, for
slopes greater than 40%
Planimetric
10 m at 90% confidence level
relative accuracy:
Altimetric
5m at 90% confidence level, for slopes
relative accuracy lower than 20%
15m at 90% confidence level, for
slopes included in 20% and 40%
28m at 90% confidence level, for
slopes greater than 40%
Table 4. Reference 3D® specifications.
When comparing all the low-resolution DTMs to the
downsampled MNT_DBTOPO®, it seems that the SRTM has a
better accuracy (μ=-0.87m, σ=5.92m, RMSE=5.99m and
LE90=8.00m) than the Cartosat-1 low-resolution aDTMs
(respectively μ=-0.41m, σ=6.47m, RMSE=6.48m, LE90=9.00m
for test#5 and μ=-1.21m, σ=6.82m, RMSE=6.93m and
LE90=10.00m for test#14), but these results may be due to an
inaccurate estimation of the elevation data in the downsampled
MNT_DBTOPO® DTM.
As expected, the Cartosat-1 low-resolution rDTMs showed
inaccurate results (μ=4.20m, σ=13.51m, RMSE=14.14m and
LE90=19.00m).
When considering the requirements for IGN’s and Spot Image’s
Reference 3D®, the Cartosat-1 low-resolution DTMs (both
relative and absolute models) met the requirements only for
slope less than 20%, while for higher slopes they did not met
the requirements.
5. CONCLUSIONS
For the Salon de Provence test site, it was fully investigated the
potentialities and limits of the 2.5m Cartosat-1 stereo images
for generating DTMs using commercial off-the-shelf software,
so from the point of view of a typical user.
When generating relative DTMs, if not properly geocoded it
was observed an error in the elevation values of some hundreds
of meters. After georeferencing, the RMSE was between 9m
and 14m and the LE90 between 16m and 19m.
When generating absolute DTMs, the optimum number of
GCPs was found to be nine, with a regular geometric
distribution (i.e., three in the upper part of the image, three in
the centre of the image and three in the lower part of the image),
while the minimum number of GCPs needed to get good DTMs
was found to be three (i.e., one in the centre, one in the lower
left and another in the lower right). In this cases, the absolute
DTMs fulfilled the standards required for the IGN’s and Spot
Image’s Reference 3D® and could be used for deriving such
product.
Finally, the comparison of the downsampled Cartosat-1 DTMs
with the NASA’s SRTM showed that the former fulfilled the
SRTM’s specifications and could be successfully used to fill
gaps in SRTM’s DTMs. A similar conclusion was also found
investigating the Mausanne les Alpilles test site (Gianinetto,
2008).
Slope
range (%)
0-20
20-40
>40
Reference 3D®
requirements (LE90)
10.00
18.00
30.00
rDTM
(LE90)
12.00
36.00
58.00
aDTM
(LE90)
6.00
14.00
27.00
Table 5. Accuracy of the Cartosat-1 relative and absolute DTMs.
Statistics on residuals (LE90) computed with respect to
Reference 3D® requirements
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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B1. Beijing 2008
ACKONWLEDGEMENTS
The author would like to thank Dr. Nandakumar (ISRO and
Secretary of ISPRS WG IV/9) for the establishment and
coordination of the ISPRS-ISRO Cartosat-1 Scientific
Assessment Programme (C-SAP) and the ISRO-ISPRS C-SAP
Evaluation Team for selecting our Institute as Investigator.
Many thanks are also addressed to Dr. Roland Gachet (IGN),
Principal-Investigator of the Salon de Provence test site, for
providing GCPs and reference MNT_DBTOPO® DTM.
Finally, the author whish to thank NASA for providing the
SRTM DTM through their website.
Indian Space Research Organisation – Signal and Image
Processing Group, 2005. Cartosat-1 (IRS – P5) Data Products
System, GeoTIFF Format for IRS Digital Data Products
(Version-2).
Indian Space Research Organisation, 2008, Cartosat-1.
http://www.isro.org/Cartosat/Page3 (accessed 25 Feb. 2008).
Krishnaswamy, M., and Kalyanaraman, S., 2002. Indian
Remote Sensing Satellite Cartosat-1: Technical features and
data
products.
GIS
Development.
http://www.gisdevelopment.net/technology/rs/techrs023.htm
(accessed 25 Feb. 2008).
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